This PhD thesis aims to move beyond the standard treatments of neighbourhoods in research on spatially transmitted inequality. The research questions explored in the four empirical chapters of the thesis delve into under-researched elements of sociospatial inequality transmission in neighbourhoods. The thesis uses statistical models to analyse register and survey data, and relies on different operationalisations of neighbourhoods: administrative and bespoke. Chapter 2 finds that controlling for selection reduces neighbourhood effects compared to when only individual characteristics are controlled for, and provides insight into the differing patterns of neighbourhood selection and effects in Dutch regional housing markets. Chapter 3 shows that the strength of the observed relationship between neighbourhood poverty and educational attainment is dependent on how exposure is measured and conceptualized, and highlights the importance of choosing the temporal aspects of individual neighbourhood histories based on the theoretical scope of a study. Chapter 4 finds that in the Netherlands, the positive effect of neighbourhood affluence on educational attainment is stronger than the negative effect of neighbourhood poverty. Chapter 5 addresses the discrepancy between the registered data-based measurements of neighbourhood characteristics, specifically the share of neighbours with foreign background and low income, and the individual perceptions of those characteristics by the inhabitants of the neighbourhood. The findings of the thesis confirm the validity of treating the neighbourhood as a social setting that interacts with the micro and macro contexts, rather than simply as an aggregated characteristic which can be controlled for.@en

Neighbourhood effects studies typically investigate the negative effects on individual outcomes of living in areas with concentrated poverty. The literature rarely pays attention to the potential beneficial effects of living in areas with concentrated affluence. This poverty paradigm might hinder our understanding of spatial context effects. Our paper uses individual geocoded data from the Netherlands to compare the effects of exposure to neighbourhood affluence and poverty on educational attainment within the same statistical models. Using bespoke neighbourhoods, we create individual neighbourhood histories which allow us to distinguish exposure effects from early childhood and adolescence. We follow an entire cohort born in 1995 and we measure their educational level in 2018. The results show that, in the Netherlands, neighbourhood affluence has a stronger effect on educational attainment than neighbourhood poverty for all the time periods studied. Additionally, interactions with parental education indicate that children with higher educated parents are not affected by neighbourhood poverty. These results highlight the need for more studies on the effects of concentrated affluence and can inspire anti-segregation policies.

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Studies of neighbourhood effects increasingly research the neighbourhood histories of individuals. It is difficult to compare the outcomes of these studies as they all use different datasets, conceptualisations and operationalisations of neighbourhood characteristics and outcome variables. This paper contributes to the literature by studying educational attainment and comparing the effects of the timing, accumulation, duration and sequencing of exposure to neighbourhood poverty. We use longitudinal register data to study the population of children born in the Netherlands in 1995 and follow them until the age of 23. Our findings show that it is important to separate the early adult years (age 18–22) when constructing individual histories of exposure to neighbourhood poverty. We find that the effect of exposure to neighbourhood deprivation on educational attainment during adolescence is slightly stronger than the effect of exposure during childhood. We conclude that the observed relationship between neighbourhood poverty and educational attainment depends on how exposure to the neighbourhood effect is conceptualised and measured; choosing just one dimension could lead to under- or overestimation of the importance of exposure to neighbourhood poverty.

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The non-random selection of people into neighbourhoods complicates the estimation of causal neighbourhood effects on individual outcomes. Measured neighbourhood effects could be the result of characteristics of the neighbourhood context, but they could also result from people selecting into neighbourhoods based on their preferences, income, and the availability of alternative housing. This paper examines how the neighbourhood effect on individual income is altered when geographic selection correction terms are added as controls, and how these results vary across three Dutch urban regions. We use a two-step approach in which we first model neighbourhood selection, and then include neighbourhood choice correction components in a model estimating neighbourhood effects on individual income. Using longitudinal register datasets for three major Dutch cities: Amsterdam, Utrecht and Rotterdam, and multilevel models, we analysed the effects for individuals who moved during a 5-year period. We show that in all cities, the effect of average neighbourhood income on individual income becomes much smaller after controlling for explicitly modelled neighbourhood selection. This suggests that studies that do not control for neighbourhood selection most likely overestimate the size of neighbourhood effects. For all models, the effects of neighbourhood income are strongest in Rotterdam, followed by Amsterdam and Utrecht.

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